Echeverria, V., Martinez-Maldonado, R., Granda, R., Chiluiza, K., Conati, C., & Buckingham Shum, S.
(2018). Driving data storytelling from learning design. In Towards user-centred learning analytics—
Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 131–140).
Association for Computing Machinery. https://doi.org/10.1145/3170358.3170380
Fernandez Nieto, G. M., Kitto, K., Buckingham Shum, S., & Martínez-Maldonado, R. (2022). Beyond the
learning analytics dashboard: Alternative ways to communicate student data insights combining
visualisation, narrative and storytelling. In Learning analytics for transition, disruption and social
change—Proceedings of the 12th International Learning Analytics and Knowledge Conference (pp.
219–229). Association for Computing Machinery. https://doi.org/10.1145/3506860.3506895
Jivet, I., Scheffel, M., Drachsler, H., & Specht, M. (2017). Awareness is not enough: Pitfalls of learning
analytics dashboards in the educational practice. In É. Lavoué, H. Drachsler, K. Verbert, J. Broisin, &
M. Pérez-Sanagustín (Eds.), Lecture notes in computer science: Vol. 10474. Data driven approaches in
digital education (pp. 82–96). Springer. https://doi.org/10.1007/978-3-319-66610-5_7
Krejtz, K., Duchowski, A. T., Niedzielska, A., Biele, C., & Krejtz, I. (2018). Eye tracking cognitive load using
pupil diameter and microsaccades with fixed gaze. PLOS ONE, 13(9), Article e0203629.
https://doi.org/10.1371/journal.pone.0203629
Lee, S., Kim, S.-H., & Kwon, B. C. (2016). VLAT: Development of a visualization literacy assessment test.
IEEE Transactions on Visualization and Computer Graphics, 23(1), 551–560.
https://doi.org/10.1109/TVCG.2016.2598920
Li, Q., Jung, Y., & Friend Wise, A. (2021). Beyond first encounters with analytics: Questions, techniques
and challenges in instructors’ sensemaking. In The impact we make: The contributions of learning
analytics to learning—Proceedings of the 11th International Conference on Learning Analytics and
Knowledge (pp. 344–353). Association for Computing Machinery.
https://doi.org/10.1145/3448139.3448172
Martinez-Maldonado, R., Echeverria, V., Fernandez Nieto, G., & Buckingham Shum, S. (2020). From data
to insights: A layered storytelling approach for multimodal learning analytics. In Proceedings of the
2020 CHI Conference on Human Factors in Computing Systems (pp. 1–15). Association for Computing
Machinery. https://doi.org/10.1145/3313831.3376148
Martinez-Maldonado, R., Pardo, A., Mirriahi, N., Yacef, K., Kay, J., & Clayphan, A. (2015). The LATUX
workflow: designing and deploying awareness tools in technology-enabled learning settings. In
Proceedings of the 5th International Conference on Learning Analytics and Knowledge (pp. 1–10).
Association for Computing Machinery. https://doi.org/10.1145/2723576.2723583
Ndukwe, I. G., & Daniel, B. K. (2020). Teaching analytics, value and tools for teacher data literacy: A
systematic and tripartite approach. International Journal of Educational Technology in Higher
Education, 17(1), 1–31. https://doi.org/10.1186/s41239-020-00201-6
Pozdniakov, S., Martinez-Maldonado, R., Tsai, Y. S., Cukurova, M., Bartindale, T., Chen, P., & Gasevic, D.
(2022). The question-driven dashboard: How can we design analytics interfaces aligned to teachers’
inquiry? In Learning analytics for transition, disruption and social change—Proceedings of the 12th
International Learning Analytics and Knowledge Conference (pp. 175–185). Association for
Computing Machinery. https://doi.org/10.1145/3506860.3506885
Pozdniakov, S., Martinez-Maldonado, R., Tsai, Y. S., Echeverria, V., Srivastava, N., & Gasevic, D. (2023).
How do teachers use dashboards enhanced with data storytelling elements according to their data
visualisation literacy skills? In Towards trustworthy learning analytics—Proceedings of the 13th
International Learning Analytics and Knowledge Conference (pp. 89–99). Association for Computing
Machinery. https://doi.org/10.1145/3576050.3576063
Schwendimann, B. A., Rodriguez-Triana, M. J., Vozniuk, A., Prieto, L. P., Boroujeni, M. S., Holzer, A.,
Gillet, D., & Dillenbourg, P. (2016). Perceiving learning at a glance: A systematic literature review of
learning dashboard research. IEEE Transactions on Learning Technologies, 10(1), 30–41.
https://doi.org/10.1109/TLT.2016.2599522
Sweller, J. (2011). Cognitive load theory. Psychology of Learning and Motivation, 55, 37–76.
https://doi.org/10.1016/B978-0-12-387691-1.00002-8
Sweller, J. (2022). The role of evolutionary psychology in our understanding of human cognition:
Consequences for cognitive load theory and instructional procedures. Educational Psychology
Review, 34(4), 2229–2241. https://doi.org/10.1007/s10648-021-09647-0